MCP server

OI AI Adoption

com.operative-intelligence/ai-adoption

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Advice on bringing AI into work processes, with sourced effects, risks and rules for SI, HR, DE, AT

Website

At a glance

Type

MCP server

Publisher

operative-intelligence.com (verified by the MCP Registry)

Status

Working at last check

Tools

8

Token cost

About 5,251 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http ai-adoption https://operative-intelligence.com/ai-adoption

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.ai-adoption]
url = "https://operative-intelligence.com/ai-adoption"

Gemini CLI

{"mcpServers":{"ai-adoption":{"httpUrl":"https://operative-intelligence.com/ai-adoption"}}}

Cursor

{"mcpServers":{"ai-adoption":{"url":"https://operative-intelligence.com/ai-adoption"}}}

VS Code

{"servers":{"ai-adoption":{"type":"http","url":"https://operative-intelligence.com/ai-adoption"}}}

Antigravity

agy mcp add ai-adoption https://operative-intelligence.com/ai-adoption

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"ai-adoption","server_url":"https://operative-intelligence.com/ai-adoption","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"ai-adoption","server_url":"https://operative-intelligence.com/ai-adoption"}

Tools

• adoption_find_patterns ~2641 tokens
  Advises on using AI in a process the user describes, from a curated knowledge base with sources. The caller passes the description, the task that best matches it and the process properties it states; the server selects deterministically and does not use a language model. The result puts questions to
• adoption_get_pattern ~375 tokens
  Returns the user-facing recommendation for one pattern (workflow, sourced effects, needs, risks, a first step) and, in an internal part, the full pattern with every claim resolved to its sources (title, publisher, URL, date read, location) and evidence level, or marked as having no source. The inter
• adoption_get_regulations ~282 tokens
  Returns the EU and national provisions in the regulation register for the chosen country, optionally only those linked to one pattern, each with what it requires in plain words, the article, the date checked and a link to the official text.
• adoption_list_process_types ~158 tokens
  Returns the six process types of the knowledge base (data capture, communication, documents, planning, control, knowledge) with a definition and the ids of the adoption patterns of each type.
• assess_ai_readiness ~245 tokens
  Scores the answers from get_readiness_questions with fixed rules: a level from 0 to 4 per area, the rule behind each limit, the gaps found and a next step for each gap. Unanswered areas are reported as not assessed. The result is a self-assessment.
• estimate_ai_costs ~1093 tokens
  Estimates the costs of introducing AI, shown separately as external costs (contractor, DPIA, legal review, AI literacy training), internal staff time, licences per month and operations per month (hosting, model usage, maintenance), and the payback period in three savings scenarios. Public data with
• get_readiness_questions ~165 tokens
  Returns the self-assessment questions on AI readiness in four areas (data, processes, people, compliance), each with its id, the reason it is asked and the allowed answer options. Answers are option ids, not free text.
• plan_ai_rollout ~292 tokens
  Returns a phased rollout plan (discovery, pilot, rollout, operations) with tasks, roles in RACI form, risks and indicators for the chosen implementation pattern. When readiness answers are given, preparation tasks for areas at level 0 or 1 are added to the discovery phase.

Browse

• Notes and wikis
• Legal research

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